Engineering Application of Artificial Intelligence

Shahab D. Mohaghegh

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Conference: 2023 ASEE North Central Section Conference
Location: Morgantown, West Virginia
Publication Date: March 24, 2023
Start Date: March 24, 2023
End Date: March 25, 2023
Page Count: 18
DOI: 10.18260/1-2--44906
Permanent URL: https://peer.asee.org/44906
Download Count: 239

Paper Authors

biography

Shahab D. Mohaghegh West Virginia University

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Shahab D. Mohaghegh, a pioneer in the application of Artificial Intelligence and Machine Learning in the Exploration and Production industry, is a Professor of Petroleum and Natural Gas Engineering at West Virginia University and the president and CEO of Intelligent Solutions, Inc. (ISI). He is the director of WVU-LEADS (Laboratory for Engineering Application of Data Science).
Including more than 30 years of research and development in the petroleum engineering application of Artificial Intelligence and Machine Learning, he has authored four books (Shale Analytics, Data-Driven Reservoir Modeling, Application of Data-Driven Analytics for the Geological Storage of CO2, Smart Proxy Modeling), more than 230 technical papers and carried out more than 60 projects for independents, NOCs and IOCs. He is an SPE Distinguished Lecturer (2007 and 2020) and has been featured four times as a Distinguished Author in SPE’s Journal of Petroleum Technology (JPT 2000 and 2005). He is the founder of SPE’s Technical Section dedicated to AI and machine learning (Petroleum Data-Driven Analytics, 2011). He has been honored by the U.S. Secretary of Energy for his AI-based technical contribution in the aftermath of the Deepwater Horizon (Macondo) incident in the Gulf of Mexico (2011) and was a member of the U.S. Secretary of Energy’s Technical Advisory Committee on Unconventional Resources in two administrations (2008-2014). He represented the United States in the International Standard Organization (ISO) on Carbon Capture and Storage technical committee (2014-2016).

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Abstract

When engineering students graduate from university, large number of them will be working for engineering industries. Artificial Intelligence and Machine Learning have a game-changing contribution to industrial and engineering-related problems. This technology will completely change the future of many industries through a transformational increase of the efficiency and accuracy of the problem solving. The contributions of Artificial Intelligence and Machine Learning to many engineering industries can be summarized in two classes: Class One: Minimization or avoidance of assumptions, interpretations, and simplifications in order to build highly realistic models of the physical phenomena. Class Two: Minimization of computational footprint of the numerical models such that they can act in a realistic and practical manner. There are major differences between modeling and solving Engineering versus Non-engineering related problems using Artificial Intelligence and Machine Learning. Successful and realistic application of Artificial Intelligence and Machine Learning in engineering disciplines requires engineering domain expertise above and beyond expertise in AI & ML. This fact challenges the current state of hypes and marketing schemes of this technology in multiple engineering disciplines. Expertise in engineering application of Artificial Intelligence is not only about understanding the mathematical characteristics of the machine learning algorithms. It is very important for engineers to know about (a) Ethics of Artificial Intelligence in engineering, (b) Expertise of Artificial Intelligence, (c) Modeling Physics using Artificial Intelligence, and (d) Differences between Artificial Intelligence and Traditional Statistics.

Citation
Format

Mohaghegh, S. D. (2023, March), Engineering Application of Artificial Intelligence Paper presented at 2023 ASEE North Central Section Conference, Morgantown, West Virginia. 10.18260/1-2--44906